CN107374609A - A kind of rhythm abnormality dynamic realtime diagnostic system - Google Patents
A kind of rhythm abnormality dynamic realtime diagnostic system Download PDFInfo
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- CN107374609A CN107374609A CN201710670131.4A CN201710670131A CN107374609A CN 107374609 A CN107374609 A CN 107374609A CN 201710670131 A CN201710670131 A CN 201710670131A CN 107374609 A CN107374609 A CN 107374609A
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
- A61B5/0004—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by the type of physiological signal transmitted
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
- A61B5/0015—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by features of the telemetry system
- A61B5/0022—Monitoring a patient using a global network, e.g. telephone networks, internet
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
- A61B5/02438—Detecting, measuring or recording pulse rate or heart rate with portable devices, e.g. worn by the patient
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7271—Specific aspects of physiological measurement analysis
- A61B5/7275—Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/74—Details of notification to user or communication with user or patient ; user input means
- A61B5/7455—Details of notification to user or communication with user or patient ; user input means characterised by tactile indication, e.g. vibration or electrical stimulation
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/74—Details of notification to user or communication with user or patient ; user input means
- A61B5/746—Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms
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- Computer Vision & Pattern Recognition (AREA)
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Abstract
The invention discloses a kind of rhythm abnormality dynamic realtime diagnostic system, including rhythm signal acquisition module and software systems, the rhythm signal acquisition module gathers user's rhythm signal, concurrently send electric terminal equipment application program to carry out subsequent treatment；The software systems include：Electric terminal equipment application program, it provides a user visualization interface on electric terminal equipment, and rhythm of the heart data are transferred into webpage background server；Webpage background server, it is responsible for the storage and management of rhythm of the heart data；PC, it carries out machine learning by rhythm signal machine learning processing module to the rhythm of the heart data of collection, train the heart rhythm conditions evaluation function of the user, dynamic realtime amendment is carried out to evaluation function according to the newest rhythm of the heart data transmitted simultaneously, user's heart rhythm conditions prediction result is provided according to evaluation function, prediction result is sent into electric terminal equipment application program to show to user, to play a part of rhythm of the heart monitoring and early warning.
Description
Technical field
The present invention is that one kind is moved using sensor technology, machine learning algorithm, the network communications technology and signal processing technology
The whether abnormal rhythm abnormality dynamic realtime diagnostic system of the state real-time diagnosis rhythm of the heart, belongs to signal synthesis processing technology field.
Background technology
The rhythm signal of human body belongs to amount complicated and changeable, close coupling, the pseudo-random event of dynamic realtime change, generally use
The mode for wearing rhythm of the heart wrist strap detects the rhythm of the heart curve of certain time period.
The existing rhythm of the heart bracelet of in the market and medical science rhythm of the heart wrist strap all simply gather the rhythm signal of certain time period, and will
Rhythm signal is directly presented to user in the form of numerical value or curve image, and measurement accuracy is low, and measuring method is heavy, and user can only
Speculate rhythm of the heart health status by carrying out the static specific rhythm of the heart situation of measurement human body, fail to obtain more from rhythm of the heart curve
More information, and existing rhythm of the heart detection method not yet detects using dynamic realtime.
The content of the invention
In order to solve problem above existing for prior art, the present invention proposes a kind of rhythm abnormality dynamic realtime diagnosis system
System, realize the application of sensor technology, the network communications technology, machine learning algorithm in the detection of rhythm abnormality dynamic realtime, profit
Rhythm of the heart data are analyzed and processed with machine learning algorithm, and therefrom train the specific heart rhythm conditions evaluation function for meeting the user,
So as to detect, analyze user's rhythm of the heart situation and play a part of when necessary early warning in real time according to the function.
The purpose of the present invention is realized by following scheme：
A kind of rhythm abnormality dynamic realtime diagnostic system, including rhythm signal acquisition module and software systems,
The rhythm signal acquisition module includes rhythm of the heart sensor, Bluetooth transmission module and wearable device；Rhythm of the heart sensor,
Bluetooth transmission module is installed on wearable device, gathers user's rhythm signal by rhythm of the heart sensor, and pass through Bluetooth transmission mould
The electric terminal equipment application program that block is sent in software systems carries out subsequent treatment；
The software systems include：
Electric terminal equipment application program, it provides a user visualization interface on electric terminal equipment, and passes through net
Network communication module is connected with visualization webpage Background communication, and rhythm of the heart data are transferred into webpage background server；
Webpage background server, itself and electric terminal equipment application program and the rhythm signal machine being embedded on PC
Learn processing module communication connection, be responsible for the storage and management of rhythm of the heart data；
PC, it carries out machine learning, training by rhythm signal machine learning processing module to the rhythm of the heart data of collection
Go out the heart rhythm conditions evaluation function of the user, while dynamic realtime is carried out to evaluation function according to the newest rhythm of the heart data transmitted and repaiied
Just, user's heart rhythm conditions prediction result is provided according to evaluation function, prediction result is sent to electric terminal equipment application program
Shown to user, to play a part of rhythm of the heart monitoring and early warning.
Further, the heart rate signal acquisition module also includes supplemental functionality, and it is arranged on wearable device, can
Auxiliary prompting function is provided a user according to user's heart rhythm conditions prediction result.
Further, the course of work of the rhythm signal machine learning processing module is as follows：
1) noise suppression preprocessing is carried out to the rhythm of the heart data received；
2) rhythm signal characteristic value is extracted, forms two-dimentional rhythm of the heart eigenmatrix；
3) convolutional neural networks computing is carried out to two-dimentional rhythm of the heart eigenmatrix；
4) row energization and pond computing are entered；
5) iterate to obtain optimal heart rhythm conditions evaluation function；
6) according to freshly harvested heart rate numerics factually when dynamic corrections heart rhythm conditions evaluation function；
7) according to heart rhythm conditions evaluation function evaluation and foreca user's heart rhythm conditions.
Invention replaces the static measurement methods such as existing wearing rhythm of the heart wrist strap, realize the dynamic realtime inspection of rhythm signal
Survey, analyze and diagnose, overcome the deficiency of static detection method comprehensively so that Detection results are more accurate.
Brief description of the drawings
Fig. 1 is overall system architecture schematic diagram of the present invention；
Fig. 2 is the rhythm signal process chart based on machine learning；
Fig. 3 is rhythm signal acquisition module structural representation；
Fig. 4 is rhythm signal denoising and feature extraction flow chart.
Embodiment
Technical scheme is discussed in detail below in conjunction with accompanying drawing：
As shown in Figure 1 to Figure 3, a kind of rhythm abnormality dynamic realtime diagnostic system, including hardware system and software systems, its
In, hardware system is rhythm signal acquisition module, and it includes：
Rhythm of the heart sensor, Bluetooth transmission module, supplemental functionality (linear vibration electric motor) and wearable device；The rhythm of the heart senses
Device, Bluetooth transmission module and linear vibration electric motor are installed on wearable device, and user's rhythm signal is gathered by rhythm of the heart sensor,
Then the electric terminal equipment application program being transmitted to by Bluetooth transmission module in software systems carries out subsequent treatment, can also basis
Need to carry out miscellaneous function expansion, for example, carrying out vibrating alert forward to user by linear vibration electric motor.
Software systems include：
Electric terminal equipment application program (uses the APP based on andriod systems) in the present embodiment, it is used in electronics
Recorded on terminal device and show heart rhythm conditions to user, electric terminal equipment application program is by network communication module and visually
Change the connection of webpage Background communication；
Webpage background server (visualization webpage backstage), it is with electric terminal equipment application program and is embedded in PC
On machine learning processing module communication connection, be responsible for data transmission；
PC (uses high-performance computer) in the present embodiment, it is by rhythm signal machine learning processing module to collection
Rhythm signal carry out a series of processing, obtain the prediction result of user's heart rhythm conditions, and it is whole that prediction result is transmitted into electron
End equipment application program is shown.
Rhythm signal collection of the present invention described in detail below and processing procedure：
First, rhythm signal acquisition module.As shown in Figure 1, 2, passed first by the rhythm signal on wearable device
Sensor, the rhythm signal of human body is gathered in real time.The acquisition module includes rhythm signal sensor, Bluetooth transmission module, linearly shaken
Dynamic motor.The rhythm of the heart data that Bluetooth transmission module is responsible for collecting are set by Bluetooth communication protocol real-time Transmission electron terminal
Rhythm of the heart data are further transferred to high-performance treatments computer by webpage background server and entered by standby application program (APP), APP
Row machine learning trains the heart rhythm conditions evaluation function of the user.Supervised in real time according to the heart rhythm conditions of function pair user
Survey, estimate and early warning, while the dynamic realtime amendment function is carried out according to the newest rhythm of the heart data transmitted.Webpage background server
APP, which is returned to, during by the fructufy of high-performance computer processing computing plays forewarning function to user's heart rhythm conditions.
2nd, rhythm signal network transmission.Rhythm signal sensor, which collects data and first passes around Bluetooth communication protocol, to be transmitted to
APP, then APP rhythm of the heart data are transferred to by webpage background server, last webpage by the http protocol of network communication module
Background server transfers data to high-performance computer by ICP/IP protocol.Wherein APP mainly provides the user one
Visualization interface, and play a part of network service terminal；Webpage background server is primarily to facilitate back-end data
Storage and management, while play a part of second-order network transfer.
3rd, rhythm signal machine learning processing module.PC carries out machine learning to rhythm of the heart data, trains the user's
Heart rhythm conditions evaluation function, while dynamic realtime amendment is carried out to evaluation function according to the newest rhythm of the heart data transmitted, according to commenting
Valency function provides user's heart rhythm conditions prediction result, and prediction result is returned into electric terminal equipment application program shows to user
Show, to play a part of rhythm of the heart monitoring and early warning, it comprises the following steps：
1) PC carries out noise suppression preprocessing to the rhythm of the heart data received first；
2) rhythm signal characteristic value is extracted, forms two-dimentional rhythm of the heart eigenmatrix；
3) convolutional neural networks computing is carried out to two-dimentional rhythm of the heart eigenmatrix；
4) row energization and pond computing are entered；
5) iterate to obtain optimal heart rhythm conditions evaluation function；
6) according to the real-time dynamic corrections heart rhythm conditions evaluation function of freshly harvested data；
7) according to function evaluation and foreca heart rhythm conditions.
As shown in figure 4, after rhythm signal enters high-performance computer, denoising is carried out first, denoising is gone using mean filter
Make an uproar some random noises.Feature extraction is carried out after denoising, the rhythm of the heart characteristic state for extracting the user forms a two-dimentional heart
Restrain eigenmatrix.Then convolutional neural networks computing is carried out to the two-dimentional rhythm of the heart eigenmatrix.By rhythm of the heart input sample.Convolution is transported
The essence of calculation is that input data and filtering matrix filter are carried out into inner product in fact.In CNN, Filter is (with one
The neuron of group fixed weight) convolutional calculation is carried out to local input data.The local number in a data window is often calculated
According to rear, the continuous translation gliding of data window, until having calculated all data.Its formula is as follows：
Rhythm of the heart data matrix passes through convolution algorithm primarily to the different characteristic of input is extracted, subsequently into Sigmoid
Function, its main function are for training for promotion speed.Sigmoid function expressions are as follows：
F (x)=(1+e-x)-1
Pond layer training is subsequently entered, pond layer would generally be respectively acting on the feature of each input and reduce its size.
Therefore the quantity of parameter and amount of calculation can also decline, and this also controls over-fitting to a certain extent.Last layer of loss function
Layer is used to determine how the difference come between the prediction result of " punishment " network and legitimate reading has reached optimal to training process
Training effect.
After training optimal heart rhythm conditions evaluation function, user can be evaluated according to the function in current slot
Whether heart rhythm conditions are abnormal so as to play a part of early warning, while the evaluation function can enter according to the rhythm of the heart data of real-time Transmission
Mobile state amendment, so as to serve the effect of rhythm abnormality dynamic realtime diagnosis.
Claims (3)
1. a kind of rhythm abnormality dynamic realtime diagnostic system, it is characterised in that including rhythm signal acquisition module and software system
System,
The rhythm signal acquisition module includes rhythm of the heart sensor, Bluetooth transmission module and wearable device；Rhythm of the heart sensor, bluetooth
Transmitter module is installed on wearable device, gathers user's rhythm signal by rhythm of the heart sensor, and send out by Bluetooth transmission module
The electric terminal equipment application program given in software systems carries out subsequent treatment；
The software systems include：
Electric terminal equipment application program, it provides a user visualization interface on electric terminal equipment, and is led to by network
News module is connected with visualization webpage Background communication, and rhythm of the heart data are transferred into webpage background server；
Webpage background server, itself and electric terminal equipment application program and the rhythm signal machine learning being embedded on PC
Processing module communication connection, is responsible for the storage and management of rhythm of the heart data；
PC, it carries out machine learning to the rhythm of the heart data of collection by rhythm signal machine learning processing module, trains this
The heart rhythm conditions evaluation function of user, while dynamic realtime amendment is carried out to evaluation function according to the newest rhythm of the heart data transmitted,
User's heart rhythm conditions prediction result is provided according to evaluation function, by prediction result be sent to electric terminal equipment application program to
Family is shown, to play a part of rhythm of the heart monitoring and early warning.
2. a kind of rhythm abnormality dynamic realtime diagnostic device as claimed in claim 1, it is characterised in that the heart rate signal is adopted
Collection module also includes supplemental functionality, and it, can be according to user's heart rhythm conditions prediction result to user on the wearable device
Auxiliary prompting function is provided.
A kind of 3. rhythm abnormality dynamic realtime diagnostic device as claimed in claim 1, it is characterised in that the rhythm signal machine
The course of work of device study processing module is as follows：
1) noise suppression preprocessing is carried out to the rhythm of the heart data received；
2) rhythm signal characteristic value is extracted, forms two-dimentional rhythm of the heart eigenmatrix；
3) convolutional neural networks computing is carried out to two-dimentional rhythm of the heart eigenmatrix；
4) row energization and pond computing are entered；
5) iterate to obtain optimal heart rhythm conditions evaluation function；
6) according to freshly harvested heart rate numerics factually when dynamic corrections heart rhythm conditions evaluation function；
7) according to heart rhythm conditions evaluation function evaluation and foreca user's heart rhythm conditions.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108392193A (en) * | 2018-01-15 | 2018-08-14 | 中科院微电子研究所昆山分所 | A kind of wearable device and its working method of real-time monitor heart rate |
| CN109243615A (en) * | 2018-10-12 | 2019-01-18 | 东软集团股份有限公司 | Determine the method, apparatus and storage medium of percussion information |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN202801606U (en) * | 2011-09-22 | 2013-03-20 | 巍世科技有限公司 | Portable electrocardiogram recording device |
| CN105534492A (en) * | 2015-11-30 | 2016-05-04 | 张胜国 | Intelligent human body sign mobile phone monitoring system |
| CN105748063A (en) * | 2016-04-25 | 2016-07-13 | 山东大学齐鲁医院 | Intelligent arrhythmia diagnosis method based on multiple-lead and convolutional neural network |
-
2017
- 2017-08-08 CN CN201710670131.4A patent/CN107374609A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202801606U (en) * | 2011-09-22 | 2013-03-20 | 巍世科技有限公司 | Portable electrocardiogram recording device |
| CN105534492A (en) * | 2015-11-30 | 2016-05-04 | 张胜国 | Intelligent human body sign mobile phone monitoring system |
| CN105748063A (en) * | 2016-04-25 | 2016-07-13 | 山东大学齐鲁医院 | Intelligent arrhythmia diagnosis method based on multiple-lead and convolutional neural network |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108392193A (en) * | 2018-01-15 | 2018-08-14 | 中科院微电子研究所昆山分所 | A kind of wearable device and its working method of real-time monitor heart rate |
| CN109243615A (en) * | 2018-10-12 | 2019-01-18 | 东软集团股份有限公司 | Determine the method, apparatus and storage medium of percussion information |
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